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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Mareeswari V Vijayan R Ashish Shukla Department of Software and Systems Engineering School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Department of Information Technology School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India Master of Computer Applications School of Computer Science Engineering and Information Systems (SCORE) Vellore Institute of Technology (VIT) Vellore India

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

Bluetooth technology, which facilitates wireless communication between Billions of devices including smartphones, tablets, laptops, and Internet of Thing (IoT) devices, is a cornerstone of modern connectivity. Its importance lies in its ability to enable seamless data exchange and interaction across a wide range of applications, from personal gadgets to complex industrial systems. Despite its widespread adoption, Bluetooth is not immune to critical security vulnerabilities. Issues like Bluetooth Low Energy (BLE) vulnerabilities and denial-of-service (DoS) attacks can overwhelm devices with excessive traffic, while BLE Forced Connection can lead to unauthorized access, and eavesdropping exposes sensitive data being exchanged. We have discussed these vulnerabilities in detail, examining their mechanisms, potential impacts, and various implementation aspects. Additionally, we have added demonstrations to illustrate how these attacks can be executed and the potential consequences. To prevent these threats, we explored essential measures, including regular firmware updates, secure pairing protocols, and careful management of Bluetooth settings. Adopting best practices like disabling Bluetooth when not in use and monitoring connected devices can further enhance security, ensuring the reliable and safe operation of the vast and growing ecosystem of Bluetooth-enabled devices.

关键词： Wireless communication Ethics Protocols Ecosystems Denial-of-service attack Security Internet of Things Bluetooth Low Energy Microprogramming Guidelines

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Fake News Detection Review: Concepts, Tools, Research GAPS, and Possible solutions

Fake News Detection Review: Concepts, Tools, Research GAPS, ...

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International Conference on Network Applications Protocols and Services (NETAPPS)

作者： Sapana Yakkundi Rudragoud Patil Swetha Indudhar Goudar Dept. of Computer Science and Engineering KLS Gogte Institute of Technology Belagavi Karnataka India Department of Computer Science and Engineering KLS Gogte Institute of Technology Belagavi Karnataka India Department. of Master of Computer Applications KLS Gogte Institute of Technology Belagavi Karnataka India

ISBN: (数字)9798331519513

ISBN: (纸本)9798331519520

The increasing number of social platforms means that there is a rapid expansion of online data. However, not all of this data can be trusted, as some users intentionally manipulate information to spread false news for personal or political reasons. Fake news can significantly impact public perception and societal outcomes. Its widespread influence was especially noticeable during the 2016 United States election cycle, leading to heated discussions about its role and consequences. Given the changing nature of news, real-time data processing has become essential for effectively identifying and countering misinformation. This research provides a comprehensive examination of the datasets, tools, and techniques utilized for detecting and combating fake news. Many researchers have developed models based on specific datasets, limiting their scope to particular domains. A thorough review of advanced models for real-time fake news detection highlights existing research gaps. The analysis of the review reveals that numerous datasets used in the literature are outdated, and there is a methodological challenge associated with the use of traditional machine learning approaches. With the continuous evolution of news, there is an urgent demand for utilizing sophisticated deep learning models for the automated, real-time verification of misinformation. This research presents promising approaches to tackle the challenge of detecting fake news.

关键词： Accuracy Protocols Limiting Reviews Social networking (online) Voting Real-time systems Data models Internet Fake news

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Image To Text Description Platform For Yakshagana Images By Detecting Crown Using CNN

Image To Text Description Platform For Yakshagana Images By ...

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Artificial Intelligence and Data Engineering (AIDE), International Conference on

作者： Kiranraj M Anantha Murthy Manish Prathwini Prathwini Savitha G Harshitha G M Department of Master of Computer Applications NMAM Institute of Technology NITTE (Deemed to be University) Nitte Karnataka India Department of Master of Computer Applications NMAM Institute of Technology NITTE (Deemed to be University) Nitte Karkala India Department of Data Science and Computer Applications Manipal Institute of Technology Manipal Academy of Higher Education Manipal

ISBN: (数字)9798331527518

ISBN: (纸本)9798331527525

This research called "Yakshakatha – Image to Text Platform for Yakshagana Images." It employs deep learning to classify crowns in Yakshagana Kirita using CNN classification. Yakshagana is a traditional South Indian art form, well known for its intricate costumes and headgear, posing specific challenges in identifying and classifying crowns. The system aims to classify various Kirita styles and provide detailed descriptions of the respective Yakshagana characters, or Vesha, offering valuable cultural and symbolic insights. The model was trained on a self-labelled dataset of Yakshagana images and used convolutional and pooling layers to capture fine details in crown designs. It achieved an impressive accuracy of 99%, ensuring precise identification and classification. Real-time predictions for the input images are made, which have predetermined mappings and description content for recognized characters. The system employs Google Gemini AI, in order to enrich the text description of the image by integrating cultural background. The responsive interface is provided for users on the image upload, real-time result, and enriched visual feedback using annotated output. This project combines modern image recognition with rich cultural content to preserve and promote the traditional heritage of Yakshagana. It will help the users to understand and appreciate the vibrancy of this art form.

关键词： Deep learning Visualization Art Image recognition Accuracy Real-time systems Robustness Cultural differences Convolutional neural networks Artificial intelligence

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Analyzing the Benefits of Applying Machine Learning to Real-Time Data Analysis 3

Analyzing the Benefits of Applying Machine Learning to Real-...

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3rd International Conference on Smart Generation Computing, Communication and Networking, SMART GENCON 2023

作者： Yadav, Rakesh Kumar Mahesh, T.R. Kumar, Ajay Jayadurga, R. Vishal, A. Sood, Gourav Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science and Engineering Karnataka Bangalore India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Prince Shri Venkateshwara Padmavathy Engineering College Department of Master of Business Administration Chennai127 India Department of Computer Engineering Vishwakarma Institute of Information Technology Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798350319125

The application of device learning to actual-time data analysis has the potential to revolutionize the way businesses make decisions. With the capacity to procedure big volumes of data fast and correctly, system learning can provide insights that tell strategic decisions at the same time as promoting information-pushed choice making. This evaluation can assist agencies increase efficiency, lower expenses, and create a more aggressive area. By means of leveraging system learning to higher recognize patron behavior, operational operations, and traits in the market, organizations can create proactive procedures to assume customer wishes and capitalize on opportunities. This paper will discover the capacity advantages of making use of device studying to actual-time records analysis and talk how businesses can satisfactory leverage it. The paper can even speak exceptional varieties of device gaining knowledge of strategies and do not forget some problems businesses need to do not forget before integrating system gaining knowledge of into their records evaluation systems. © 2023 IEEE.

关键词： businesses Evaluation exceptional forget records

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Exploring the Approaches to Secure Mobile Devices in Wireless Networks 15

Exploring the Approaches to Secure Mobile Devices in Wireles...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Pandian, Rajesh Garima Jayadurga, R. Karnik, Madhuri P. Grover, Madhur Naval, Preeti Karnataka Bangalore India Department of Computer Science & Engineering Vivekananda Global University Jaipur India Department of Master of Business Administration Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Department of Computer Engineering Vishwakarma Institute of Technology Pune India Centre of Interdisciplinary Research in Business and Technology Chitkara University Institute of Engineering and technology Chitkara University Punjab India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350370249

This paper explores various approaches used to relaxed mobile devices from intrusions in wireless networks. The contemporary strategies contemporary security, inclusive of encryption, authentication and authorization strategies, is discussed in detail. The advantages and downsides latest approach are mentioned to decide the satisfactory technique for mobile tool safety. Furthermore, numerous emerging security measures such as the ones primarily based on biometrics and context-consciousness are evaluated and compared. The abilities and obstacles trendy method are analyzed relative to these options. These research paper goals to discover new possibilities for security contemporary cell devices in Wi-Fi networks for reinforcing relaxed facts transactions and conversation. The paper outlines the contribution contemporary security methods to enhance the security degree cutting-edge cellular devices, and suggest effective strategies to defend towards capability security threats. Similarly, the paper will offer an in-depth survey present day security technology and their implementation challenges in the wireless domestic community surroundings. ©2024 IEEE.

关键词： Network intrusion

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An Analysis of the Impact of DNS-Based Authentication on Wireless Network Security 1

An Analysis of the Impact of DNS-Based Authentication on Wir...

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1st IEEE International Conference on Emerging Research in Computational science, ICERCS 2023

作者： Gawali, Piyush P. Das, Neeraj Rajesh, A. Shukla, Anupam Sohal, Jagmeet Jayadurga, R. Vishwakarma Institute of Information Technology Department of Computer Engineering Pune India Maharishi University of Information Technology Maharishi School of Engineering and Technology Uttar Pradesh India Faculty of Engineering and Technology Department of Computer Science Engineering Karnataka Bangalore India Vivekananda Global University Department of Computer Science & Engineering Jaipur India Chitkara University Institute of Engineering and Technology Chitkara University Centre of Interdisciplinary Research in Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Master of Business Administration Chennai127 India

ISBN: (纸本)9798350359756

This paper investigates the effect of DNS-primarily based authentication on wireless network safety. DNS-primarily based authentication is used to authenticate consumer credentials on Wi-Fi networks, generally primarily based upon the Dynamic Host Configuration Protocol (DHCP). The research specializes in checking out the authentication system via numerous simulations, reading the performance and security of the authentication manner. Effects from such studies monitor that the usage of DNS-based total authentication can improve the safety of a Wi-Fi community, specifically in mitigating man-in-the-center assaults. In addition, analysis shows that DNS-based authentication concurrently improves network overall performance using reducing the fee of authentication, decreasing latency, and increasing the scalability of the authentication process. This research suggests that universal, DNS-based authentication is a precious tool to enhance the security of Wi-Fi networks. © 2023 IEEE.

关键词： Authentication

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Exploring the predictive potential of artificial neural networks in enhancing mechanical properties of derivatives of graphene nanocomposites: a data-driven approach

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International Journal of Information technology (Singapore) 2025年第2期17卷 999-1005页

作者： Rao, D. Nageswara Dahiya, Mamta Arora, Amit Kumar Jandwani, Paras Verma, Gunjan CSE ACED Alliance University Chikkahagade cross Anekal Bangalore India MAIT Maharaja Agrasen University Himachal Pradesh Solan India Computer Science and Engineering IIT Madras Chennai India Accenture LLP Philadelphia PA United States Dept. of Master of Computer Applications G L Bajaj Institute of Technology and Management Uttar Pradesh Greater Noida India

The given manuscript delves into the realm of materials science and engineering, specifically focusing on the utilization of different derivatives of graphene reinforced in matrix material (DGMM’s) to enhance mechanical properties. Graphene (Gr), with its remarkable characteristics, holds immense promise as reinforcement in composites and nanocomposites (NCs). Using linear regression and artificial neural networks (ANN) framework, this study predicts the weight% of enhanced mechanical properties in DGMMs. By analyzing a dataset comprising various graphene derivatives, matrix materials, processing methods, and resulting enhancements, the ANN model offers valuable insights into the intricate relationships within these NCs. The findings reveal the potential of ANN models in optimizing the design and fabrication processes of DGMMs, thereby accelerating materials development and enabling tailored formulations for specific applications. Also, the given manuscript motivates for future research to enhance the predictive accuracy and broaden the scope of applications for *** confirm the corresponding author is correctly identified and amend if ***, it is *** confirm the inserted city name is correct in Affiliation (3, 4) and amend if ***, it is correct and confirmed © Bharati Vidyapeeth's institute of computer Applications and Management 2024.

关键词： Artificial neural networks Graphene Linear regression Nanocomposites Nanomaterial

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A Survey on Privacy-Preserving Federated Learning in Internet of Things (IoT)

A Survey on Privacy-Preserving Federated Learning in Interne...

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Next Generation Communication & Information Processing (INCIP), International Conference on

作者： S. Raghav B. Vamsi Krishna Vanipriya Ch Department of Computer Science and Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Department of Master of Computer Applications Sir M Visvesvaraya Institute of Technology Bengaluru India

ISBN: (数字)9798331528140

ISBN: (纸本)9798331528157

This survey article provides a comprehensive overview of Privacy-preserving Federated Learning (FL) in the Internet of Things (IoT), focusing on secure collaborative learning with distributed data. In response to the proliferation of IoT devices generating vast amounts of sensitive information, the survey delves into state-of-the-art methodologies and technologies aimed at preserving user privacy during collaborative model training. The review encompasses cryptographic techniques, secure aggregation protocols, and differential privacy mechanisms, addressing the unique challenges posed by decentralized and heterogeneous IoT environments. Through an analysis of communication overhead, resource constraints, and device diversity, the survey offers a nuanced understanding of the current landscape, including optimization strategies and emerging trends. Serving as a valuable resource for researchers and practitioners, this survey not only synthesizes existing knowledge but also identifies research gaps and proposes potential directions for advancing secure collaborative learning in IoT through Privacy-Preserving Federated Learning.

关键词： Surveys Training Differential privacy Federated learning Reviews Scalability Malware Blockchains Internet of Things Optimization

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Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments 6

Deep Reinforcement Learning-based Obstacle Avoidance for Rob...

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6th IEEE International Conference on Civil Aviation Safety and Information technology, ICCASIT 2024

作者： Li, Keqin Chen, Jiajing Yu, Dezhi Dajun, Tao Qiu, Xinyu Lian, Jieting Ji, Ryan Zhang, Shengyuan Wan, Zhenyu Sun, Baiwei Hong, Bo Ni, Fanghao Han, Jiaqi Ama University Department of Computer Science Quezon Philippines Courant Institute New York University 251 Mercer St New YorkNY10012 United States University of California Berkeley University Avenue and Oxford St School of Information BerkeleyCA94720 United States Carnegie Mellon University Master of Science in Mechanical Engineering School of Engineering 5000 Forbes Avenue PittsburghPA United States Northeastern University College of Engineering Seattle United States School of Professional Studies New York University Master of Science in Database Technology 50 West 4th Street New YorkNY United States Cornell University College of Engineering 616 Thurston Ave IthacaNY14853 United States Cornell University Master of Professional Science in Applied Statistics-Data Science College of Computing and Information Science 616 Thurston Ave IthacaNY United States Independent Researcher Beijing China University of California Irvine Master of Computer Science Donald Bren School of Information and Computer Sciences 510 Aldrich Hall IrvineCA United States Northern Arizona University School of Informatics Computing and Cyber Systems FlagstaffAZ United States Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9798350389418

This paper proposes a deep reinforcement learning based on the warehouse environment, the mobile robot obstacle avoidance Algorithm. Firstly, the value function network is improved based on the pedestrian interaction. We can learn to obtain the relative importance of the current state and the historical trajectory state as well as the joint impact on the robot's obstacle avoidance strategy. Secondly, the reward function of reinforcement learning is designed based on the spatial behaviour of pedestrians, and the robot is punished for the state where the angle changes too much, so as to achieve the requirement of comfortable obstacle avoidance. Finally, the feasibility and effectiveness of the deep reinforcement learning-based mobile robot obstacle avoidance algorithm in the warehouse environment in the complex environment of the warehouse are verified through simulation experiments. © 2024 IEEE.

关键词： Deep reinforcement learning

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Analogous Particle Swarm Optimization for Choosing Optimal Selection of Virtual Machine in Cloud 12

Analogous Particle Swarm Optimization for Choosing Optimal S...

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12th International Conference on computer Communication and Informatics, ICCCI 2022

作者： Kumar, R. Prasanna Vignesh, T. Venkateswarulu, Balaji Vijayan Sivakumar, R. Amrita School of Engineering Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Vidyapeetham Chennai India Srm Institute of Science and Technology Department of Master of Computer Application Chennai Ramapuram India Vignan's Foundation for Science Technology and Research Department of Computer Science and Engineering Vadlamudi AP Guntur India Easwari Engineering College Dept of Physics Chennai Ramapuram India

ISBN: (纸本)9781665480352

Cloud computing is one of the chief elements in Medical Care Administrations. It tends to be utilized to recover data about patients, their records identified with diagnosing, therapy taken and other clinical data in less measure of time. In this field picking of an ideal VM is a difficult and more intriguing in medical care administrations. The way to deal with pick the best ideal VM helps in expanding the exhibition of medical care benefits consequently decreasing the running opportunity to execute the solicitation. This paper proposes a novel and upgraded rendition of PSO called Similar to Molecule Multitude Enhancement (APSO). The presentation is contrasted and Hereditary Calculation and PSO. The assessment is finished by considering three boundaries like holding up time, use of computer chip and turnaround time. The outcomes unmistakably express that the APSO approach performs well when contrasted with different models. The general execution time for every molecule is registered as 1s and effectiveness apparently is improved by 5.6%. © 2022 IEEE.

关键词： Genetic algorithms

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